The subject matter discussed in the background section should not be assumed to be prior art merely as a result of its mention in the background section. Similarly, a problem mentioned in the background section or associated with the subject matter of the background section should not be assumed to have been previously recognized in the prior art. The subject matter in the background section merely represents different approaches, which in and of themselves may also be inventions.
Companies are often overwhelmed with customer data. Names, titles, billing addresses, shipping addresses, email addresses, phone numbers, household data, affiliated companies, and associated parties are examples of customer data fields. Managing customer data can become extremely complex and dynamic due to the many changes individual customers go through over time. Multiply all of these customer data fields by the millions of customer data records which a company may have in its data sources, and factor in how quickly and how often this customer data changes, and the result is that many companies have a significant data management challenge.
Some customer data providers attempt to address this challenge by using a crowd-sourced platform to build a contact database which is sourced and updated by sales and marketing professionals. However, the customer data provided by customer data providers often has a variety problems, such as invalid email addresses or invalid phone numbers, a contact record with incorrect information from a name spelled wrong to a bad address, incomplete or inaccurate records for company names, job titles, and phone numbers, non-current data, wrong company information or wrong contact data, duplicate contacts with inconsistent information, fields that are empty due to poor data capture techniques or contain other inaccurate information, completed fields that contain nonsense data such as “TBA” or “TBD,” and outdated information, such as a contact that no longer works at the contact's former company. Customer data providers may have these problems because community update models treat every add request or update request as an absolute fact, which can potentially lead to bad updates, such as incorrectly inactivating high-profile executives or fraudulently adding bogus contacts. While some issues may be alleviated by adding carrot-and-stick safeguards such as penalties for bad updates, rewards for good updates, and reputation-based updates, only a few ill-intentioned users can undermine the quality of customer data. Furthermore, the potential for bad data still exists when millions of records enter a customer data provider system from other sources, such that users or partners may end up adding bad data unknowingly from outdated lists and databases.